AI
"AI Without Workflows Is Just Expensive Advice": Advisory vs Agentic AI
There's a single sentence that explains why most enterprise AI budgets aren't producing the returns the board was promised. ServiceNow's Terence Chesire said it plainly: "AI without workflows is just expensive advice." Reworked
There's a single sentence that explains why most enterprise AI budgets aren't producing the returns the board was promised. ServiceNow's Terence Chesire said it plainly: "AI without workflows is just expensive advice." Reworked
Read that twice, because it's the whole 2026 enterprise AI debate compressed into six words.
01
The advisory ceiling
ServiceNow's argument is that most enterprise AI to date has been advisory — it summarizes, drafts and recommends, but humans still do the work. That's not worthless. But it has a hard ceiling: every advisory interaction still needs a human to translate the suggestion into a completed action. You've added an assistant, not capacity. The cost is real and recurring; the productivity is bounded by the humans downstream. Reworked
This is why so many AI pilots show great demos and flat business cases. The model is impressive. The workflow never closed.
02
What "agentic" actually means
The distinction ServiceNow draws is that its specialists complete end-to-end processes rather than stopping at advice. These AI specialists are assigned to roles, with business context and permissions, to handle complex workflows end-to-end — not isolated tasks. The unit of value shifts from "a better suggestion" to "a finished outcome with no human in the loop for the routine path." ReworkedServiceNow
That's the leap. And it's also where the risk profile changes completely.
03
Why the distinction is also a governance line
An advisory agent that's wrong wastes a few minutes. An agentic one that's wrong executed something. The moment AI moves from recommending to completing work, three questions become non-negotiable: What is this agent permitted to do? Can we see what it did? Can we stop or reverse it? Advisory AI lets you defer those questions. Agentic AI does not.
This is the part vendors selling you autonomy tend to soft-pedal. The value of agentic AI is exactly proportional to how much you let it act unsupervised — and so is the exposure. You don't get the upside without accepting the accountability problem. The enterprises that win aren't the ones most aggressive about autonomy; they're the ones that made autonomy auditable so they could actually turn it on.
04
The honest takeaway
If your AI program is still advisory, you have a productivity ceiling. If it's going agentic, you have a governance obligation. Most enterprises are about to discover both at the same time. The order you address them in determines whether the next 18 months are a competitive advantage or an incident report.
[CTA: Find out where your AI sits on the advisory-to-agentic curve — and what governance you need before you cross.]
